Identification (biology)

Physics

Business

Pure mathematics

Value (mathematics)

Risk management

Dimension (graph theory)

Mathematics

Operations research

Categorical variable

Biology

Financial economics

Matrix (chemical analysis)

Psychoanalysis

Risk analysis (engineering)

Machine learning

Management

Psychology

Composite material

Economics

Materials science

Scale (ratio)

Portfolio

Computer science

Botany

Quantum mechanics

Value at risk

Attractiveness

International Journal of Information Technology & Decision Making

Risk matrices are adopted and recommended by many organizations, but the way they are usually constructed violates some basic theoretical principles, giving rise to inconsistent risk ratings. This paper studies ways in which multiple criteria and portfolio decision analyses can improve the design and deployment of risk matrices, using MACBETH (the “Measuring Attractiveness by a Categorical Based Evaluation TecHnique”). Firstly, it introduces ‘value risk-matrices’, built with MACBETH in the following modeling steps: (1) building a value measurement scale on each impact dimension and constructing a subjective probability scale, (2) additive aggregation of the value scales into a cumulative value scale, and (3) design of the value risk-matrix. The value and probability scores of risks are plotted in the matrix and its analysis informs the identification of mitigation actions, which can then be prioritized making use of the recent portfolio module of the MACBETH decision support system. Taken all together, the paper sketches a new modeling approach for Improving Risk Matrice s (IRIS).

Designing and exploring risk matrices with MACBETH